Instructions to use fancyfeast/joytag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fancyfeast/joytag with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="fancyfeast/joytag") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fancyfeast/joytag", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8cc0cba7906d7848e4318354f8759f43ce2921295f92b47960c3ccc8525cc898
- Size of remote file:
- 366 MB
- SHA256:
- f85b7130e6e549b5b0822537007b7482e8c4c8e754c8d9a5bee08e27050e1097
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